Newborn EEG simulation from nonlinear analysis

In this paper, we propose a novel method of simulating normal newborn EEG. The method is based on the results from the fractal dimension analysis of real EEG recordings. The fractal dimension analysis was done using the Higuchi method for fractal dimension estimation. Comparison of signals in the time domain, frequency domain and time-frequency domain between real and simulated signals show similarities validating the EEG simulator. This model can provide artefact free EEG signals for researchers so that algorithm parameters can be tuned or so that automatic EEG detection algorithms, such as seizure detection and epileptic spike detection, can be evaluated.